diff --git a/CLPBN/learning/em.yap b/CLPBN/learning/em.yap
index b723cf182..9d1d4fa07 100644
--- a/CLPBN/learning/em.yap
+++ b/CLPBN/learning/em.yap
@@ -8,13 +8,15 @@
 	      [append/3]).
 
 :- use_module(library(clpbn),
-	      [clpbn_init_solver/3,
-	       clpbn_run_solver/3]).
+	      [clpbn_init_solver/5,
+	       clpbn_run_solver/4,
+	       clpbn_flag/2]).
 
 :- use_module(library('clpbn/dists'),
 	      [get_dist_domain_size/2,
 	       empty_dist/2,
-	       dist_new_table/2]).
+	       dist_new_table/2,
+	       get_dist_key/2]).
 
 :- use_module(library('clpbn/connected'),
 	      [clpbn_subgraphs/2]).
@@ -33,6 +35,11 @@
 	      [matrix_add/3,
 	       matrix_to_list/2]).
 
+:- use_module(library(rbtrees),
+	      [rb_new/1,
+	       rb_insert/4,
+	       rb_lookup/3]).
+
 :- use_module(library('clpbn/utils'),
 	      [
 	       check_for_hidden_vars/3,
@@ -53,14 +60,15 @@ em(Items, MaxError, MaxIts, Tables, Likelihood) :-
 % it includes the list of variables without evidence,
 % the list of distributions for which we want to compute parameters,
 % and more detailed info on distributions, namely with a list of all instances for the distribution.
-init_em(Items, state(AllVars, AllDists, AllDistInstances, MargVars)) :-
+init_em(Items, state( AllDists, AllDistInstances, MargVars, SolverVars)) :-
 	run_all(Items),
 	attributes:all_attvars(AllVars0),
 	sort_vars_by_key(AllVars0,AllVars1,[]),
 	% remove variables that do not have to do with this query.
 	check_for_hidden_vars(AllVars1, AllVars1, AllVars),
 	different_dists(AllVars, AllDists, AllDistInstances, MargVars),
-	clpbn_init_solver(MargVars, AllVars, _).
+	clpbn_flag(em_solver, Solver),
+	clpbn_init_solver(Solver, MargVars, AllVars, _, SolverVars).
 
 % loop for as long as you want.
 em_loop(Its, Likelihood0, State, MaxError, MaxIts, LikelihoodF, FTables) :-
@@ -82,8 +90,9 @@ em_loop(Its, Likelihood0, State, MaxError, MaxIts, LikelihoodF, FTables) :-
 	).
 
 ltables([], []).
-ltables([Id-T|Tables], [Id-LTable|FTables]) :-
+ltables([Id-T|Tables], [Key-LTable|FTables]) :-
 	matrix_to_list(T,LTable),
+	get_dist_key(Id, Key),
 	ltables(Tables, FTables).
 	 
 
@@ -92,7 +101,8 @@ ltables([Id-T|Tables], [Id-LTable|FTables]) :-
 different_dists(AllVars, AllDists, AllInfo, MargVars) :-
 	all_dists(AllVars, Dists0),
 	sort(Dists0, Dists1),
-	group(Dists1, AllDists, AllInfo, MargVars, []).
+	group(Dists1, AllDists, AllInfo, MargVars0, []),
+	sort(MargVars0, MargVars).
 
 all_dists([], []).
 all_dists([V|AllVars], [i(Id, [V|Parents], Cases, Hiddens)|Dists]) :-
@@ -143,30 +153,46 @@ same_id([i(Id,Vs,Cases,Hs)|Dists1], Id, [i(Id, Vs, Cases, Hs)|Extra], Rest) -->
 	same_id(Dists1, Id, Extra, Rest).
 same_id(Dists, _, [], Dists) --> [].
 
-estimate(state(Vars, _, _, Margs), LPs) :-
-	clpbn_run_solver(Margs, Vars, LPs).
 
-maximise(state(_,_,DistInstances,_), Tables, LPs, Likelihood) :-
-	compute_parameters(DistInstances, Tables, LPs, 0.0, Likelihood).
+compact_mvars([], []).
+compact_mvars([X1,X2|MargVars], CMVars) :- X1 == X2, !,
+	compact_mvars([X2|MargVars], CMVars).
+compact_mvars([X|MargVars], [X|CMVars]) :- !,
+	compact_mvars(MargVars, CMVars).
 
-compute_parameters([], [], [], Lik, Lik).
-compute_parameters([Id-Samples|Dists], [Id-NewTable|Tables], Ps, Lik0, Lik) :-
+estimate(state(_, _, Margs, SolverState), LPs) :-
+	clpbn_flag(em_solver, Solver),
+	clpbn_run_solver(Solver, Margs, LPs, SolverState).
+
+maximise(state(_,DistInstances,MargVars,_), Tables, LPs, Likelihood) :-
+	rb_new(MDistTable0),
+	create_mdist_table(MargVars,LPs,MDistTable0,MDistTable),
+	compute_parameters(DistInstances, Tables, MDistTable, 0.0, Likelihood).
+
+create_mdist_table([],[],MDistTable,MDistTable).
+create_mdist_table([Vs|MargVars],[Ps|LPs],MDistTable0,MDistTable) :-
+	rb_insert(MDistTable0, Vs, Ps, MDistTableI),
+	create_mdist_table(MargVars, LPs, MDistTableI ,MDistTable).
+
+compute_parameters([], [], _, Lik, Lik).
+compute_parameters([Id-Samples|Dists], [Id-NewTable|Tables],  MDistTable, Lik0, Lik) :-
 	empty_dist(Id, Table0),
-	add_samples(Samples, Table0, Ps, MorePs),
+	add_samples(Samples, Table0, MDistTable),
 	soften_sample(Table0, SoftenedTable),
 	normalise_counts(SoftenedTable, NewTable),
 	compute_likelihood(Table0, NewTable, DeltaLik),
 	dist_new_table(Id, NewTable),
 	NewLik is Lik0+DeltaLik,
-	compute_parameters(Dists, Tables, MorePs, NewLik, Lik).
+	compute_parameters(Dists, Tables,  MDistTable, NewLik, Lik).
 
-add_samples([], _, Ps, Ps).
-add_samples([i(_,_,[Case],[])|Samples], Table, AllPs, RPs) :- !,
+add_samples([], _, _).
+add_samples([i(_,_,[Case],[])|Samples], Table, MDistTable) :- !,
 	matrix_add(Table,Case,1.0),
-	add_samples(Samples, Table, AllPs, RPs).
-add_samples([i(_,_,Cases,_)|Samples], Table, [Ps|AllPs], RPs) :-
+	add_samples(Samples, Table, MDistTable).
+add_samples([i(_,_,Cases,Hiddens)|Samples], Table, MDistTable) :-
+	rb_lookup(Hiddens, Ps, MDistTable),
 	run_sample(Cases, Ps, Table),
-	add_samples(Samples, Table, AllPs, RPs).
+	add_samples(Samples, Table, MDistTable).
 
 run_sample([], [], _).
 run_sample([C|Cases], [P|Ps], Table) :-